Vegetation Model Research Articles

Effects of In Vivo Contact Force on Pulsed-Field Ablation Efficacy in Porcine Ventricles.

Pulsed-field ablation (PFA) is an innovative non-thermal method for arrhythmia treatment. The efficacy of various PFA configurations in relation to contact force (CF) has not been well-studied in vivo. This study evaluated the effect of CF on acute bipolar PFA lesions in both a vegetal and an in vivo porcine heart model. Bipolar PFA (500 V, 20 μs for 50 pulses) was applied to eight porcine ventricles, with CF categorized as standard (5-15 g), high (16-30 g), or very high (> 30 g) using the CARTO 3 system. PFA lesions were assessed by gross pathology, histology, and post-ablation voltage amplitude. Additionally, a vegetal model using oscillating russet potatoes replicated the motion of a beating heart to compare lesion parameters under dynamic conditions and various PFA configurations (monopolar vs. bipolar). A total of 61 in vivo bipolar PFA lesions across all groups were analyzed. No significant differences in lesion surface diameter, depth, or volume were found among CF groups. In the vegetal model, monopolar setting had a better correlation between CF and lesion depth compared to bipolar setting. In addition, oscillations and catheter position (perpendicular or parallel) significantly affected lesion dimensions. Increasing CF has a minimal effect on the size of acute bipolar PFA lesions in the porcine ventricle, suggesting that, for bipolar PFA, adequate CF is more critical than its intensity in a beating heart. For monopolar PFA, greater CF can impact lesion depth.

EutherianCoP. An integrated biotic and climate database for conservation paleobiology based on eutherian mammals

We present a new database, EutherianCoP, of fossil mammals which lived globally from the Late Pleistocene to the Holocene. The database includes 13,972 fossil occurrences of 786 extant or recently extinct placental mammal species, plus 155,198 current occurrences for those of them which survived to the present. The occurrences are correlated with radiometric age information. For all species, we provide 32 different traits, inclusive of taxonomic, phenotypic, life history, biogeographic and phylogenetic information. Differently from any other compilation, the occurrences are complemented with estimates of past climatic conditions, including site-interpolated monthly and annual precipitation and temperature, leaf area index, megabiome type and net primary productivity, which are derived from transient paleo model simulations conducted with the Community Earth System Model 1.2 and the BIOME4 vegetation model. All data are further downloadable for further investigation.

A unifying principle for global greenness patterns and trends

Vegetation cover regulates the exchanges of energy, water and carbon between land and atmosphere. Remotely-sensed fractional absorbed photosynthetically active radiation (fAPAR), a land-surface greenness measure, depends on carbon allocation to foliage while also controlling photon flux for photosynthesis. Here we use an equation with just two globally fitted parameters to describe annual maximum fAPAR as the smaller of a water-limited value transpiring a constant fraction of annual precipitation, and an energy-limited value maximizing annual plant growth. This minimalist description reproduces global greenness patterns and temporal trends in remote-sensing data, comparable to the best-performing dynamic global vegetation models. Widely observed greening is attributed principally to the influence of rising carbon dioxide on the light- and water-use efficiencies of photosynthesis; limited browning regions are attributed to drying. This research provides one key component of ecosystem function as a step towards more robust foundations for new-generation land ecosystem models.

Atmospheric nitrogen oxides (NOx), hydrogen sulphide (H2S) and carbon monoxide (CO): Boon or Bane for plant metabolism and development?

Urban air pollution has been a global challenge world-wide. While urban vegetation or forest modelling can be useful in reducing the toxicities of the atmospheric gases by their absorption, the surge in gaseous pollutants negatively affects plant growth, thereby altering photosynthetic efficiency and harvest index. The present review analyses our current understanding of the toxic and beneficial effects of atmospheric nitrogen oxides (NOx), hydrogen sulphide (H2S) and carbon monoxide (CO) on plant growth and metabolism. The atmospheric levels of these gases vary considerably due to urbanization, automobile emission, volcanic eruptions, agricultural practices and other anthropological activities. These gaseous pollutants prevalent in the atmosphere are known for their dual action (toxic or beneficiary) on plant growth, development and metabolism. NO seems to exert a specialized impact by upregulating nitrogen metabolism and reducing tropospheric ozone. High H2S emission in specific areas of geothermal plants, fumarolic soils and wetlands can be a limitation to air quality control. Certain shortcomings associated with the designing of field experiments, sensitivity of detection methods and simulation development are yet to be overcome to analyze the precise levels of NO, H2S and CO in the rhizosphere of diverse agro-climatic regions. Several laboratory-based investigations have been undertaken to assess the roles of atmospheric gases, namely NOx, CO, H2S, and particulate matter (PM). However, in order to enable natural and sustainable mitigation, it is essential to increase the number of field experiments in order to identify the pollutant-tolerant plants and study their interactive impact on plant growth and agriculture.

Impacts of the Russia–Ukraine war on the welfare of palm oil producers and consumers in Indonesia

PurposeThis research aims to examine the impacts of the Russia–Ukraine war on the welfare of Indonesian palm oil producers and consumers.Design/methodology/approachThe research uses time-series data from 2000 to 2022 for inferential, simulation and descriptive analyses, coupled with a world vegetable oil trade model in the form of a system of simultaneous equations. The two-stage least squares (2SLS) estimation method with 37 simultaneous equations is used to estimate parameters.FindingsThe research results show that the Russia–Ukraine conflict has led to an increase in the welfare of Indonesian palm oil producers and consumers. A combination of domestic policies (replanting, export tax, mandatory biodiesel and domestic market obligation) has boosted Indonesian palm oil industry players welfare after the Russia–Ukraine conflict. On the other hand, it caused a decline in the welfare of cooking oil and biodiesel producers due to the surge in raw material costs and the decline in selling prices. Therefore, market differentiation for palm oil derivative products into international markets is required.Originality/valueThe results of this research provide empirical evidence to the Indonesian government regarding the importance of policies that regulate the demand and supply of palm oil compared to increasing palm oil production. The results of this research emphasize that the development of policies for the Indonesian palm oil industry needs to pay attention to global vegetable oil market fluctuations as well as the importance of holistic policies from the on-farm to the off-farm level to ensure that producers and consumers experience increased welfare.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2024-0531

Quantifying the Impact of Climate Change and Forest Management on Swedish Forest Ecosystems Using the Dynamic Vegetation Model LPJ‐GUESS

AbstractBoreal and temperate forests are undergoing structural, compositional and functional changes in response to increasing temperatures, changes in precipitation, and rising CO2, but the extent of the changes in forests will also depend on current and future forest management. This study utilized the dynamic vegetation model LPJ‐GUESS enabled with forest management (version 4.1.2, rev11016) to simulate changes in forest ecosystem functioning and supply of ecosystem services in Sweden. We compared three alternative forest policy scenarios: Business As Usual, with no change in the proportion of forest types within landscapes; Adaptation and Resistance, with an increased area of mixed stands; and EU‐Policy, with a focus on conservation and reduced management intensity. LPJ‐GUESS was forced with climate data derived from an ensemble of three earth system models to study long‐term implications of a low (SSP1‐2.6), a high (SSP3‐7.0), and a very high (SSP5‐8.5) emissions scenario. Increases in net primary production varied between 4% and 8% in SSP1‐2.6, 21%–25% in SSP3‐7.0 and 25%–29% in SSP5‐8.5 across all three forest policy scenarios, when comparing 2081–2100 to 2001–2020. Increased net primary production was mediated by a higher soil nitrogen availability and increased water use efficiency in the higher emission scenarios SSP3‐7.0 and SSP5‐8.5. Soil carbon storage showed small but significant decreases in SSP3‐7.0 and in SSP5‐8.5. Our results highlight differences in the predisposition to storm damage among forest policy scenarios, which were most pronounced in southern Sweden, with increases of 61%–76% in Business‐As‐Usual, 4%–11% in Adaptation and Resistance, and decreases of 7%–12% in EU‐Policy when comparing 2081–2100 to 2001–2020.

Comparison of Global Aboveground Biomass Estimates From Satellite Observations and Dynamic Global Vegetation Models

AbstractThe global forest carbon stocks represent the amount of carbon stored in woody vegetation and are important for quantifying the ability of the global forests to sequester atmospheric CO2 and to provide ecosystem services (e.g., timber) under climate change. The forest ecosystem carbon pool estimates are highly variable and poorly quantified in areas lacking forest inventory estimates. Here, we compare and analyze aboveground biomass (AGB) estimates from five satellite‐based global data sets and nine dynamic global vegetation models (DVGMs). We find that across the data sets, mean AGB exhibits the largest variability around the tropical area. In addition, AGB shows a similar latitudinal trend but large variability among the data sets. Satellite‐based AGB estimates are lower than those simulated by DVGMs. The divergence among the satellite‐based AGB estimates can be driven by the methodology, input satellite products, and the forested areas used to estimate AGB. The modeled NPP, autotrophic respiration, and carbon allocation mostly drive the variability of AGB simulated by DGVMs. The future availability of a high‐quality global forest area map is anticipated to improve AGB estimate accuracy and to reduce the discrepancies among different satellite‐ and model‐based AGB estimates. We suggest the carbon‐modeling community reexamine the methodology used to estimate AGB and forested areas for a more robust global forest carbon stock estimation.

Biogenic CO2 flux uncertainty: numerical experiments and validation over south-eastern South America

Understanding carbon dioxide (CO2) surface fluxes is essential in the context of a changing climate. In particular, agriculture significantly contributes to CO2 fluxes. Recently, some studies have focused on understanding how synoptic-scale variability modulates CO2 fluxes associated with vegetation and agriculture, finding that frontal passages and precipitation events exert a strong influence on these fluxes. This variability is particularly relevant in the Argentinean Pampas, where large CO2 fluxes associated with extensive agriculture combine with strong synoptic variability. Numerical modelling provides a valuable tool for investigating surface CO2 fluxes and their variability, despite the uncertainties associated with the model’s limitations. In this work, we investigate simulated CO2 fluxes in the Argentinean Pampas using the Weather Research and Forecasting Model (WRF) coupled with the Vegetation, Respiration and Photosynthesis Model (VPRM) over three case studies representing different synoptic-scale conditions. In addition, we estimate the uncertainty in the simulations by comparing simulated CO2 fluxes using various WRF configurations and the ERA5 reanalysis. We found that the synoptic-scale conditions have a considerable impact on the magnitude of fluxes as well as the simulation uncertainty. Uncertainties in simulated CO2 fluxes can be as high as 60%, being larger at sunrise and sunset. Also, the largest uncertainty is associated with a case with a cold frontal passage and widespread precipitation. These results allow a more accurate estimation of CO2 flux uncertainty, which is key to understanding the effects of climate change.

Vegetation Dynamics and Recovery Potential in Arid and Semi-Arid Northwest China.

The arid and semi-arid regions of northwest China are characterized by sparse vegetation and fragile ecosystems, making them highly susceptible to the impacts of climate change and human activities. Based on observed meteorological data, the Normalized Difference Vegetation Index (NDVI), the Lund-Potsdam-Jena dynamic global vegetation model (LPJ), a vegetation recovery potential model, and the MK trend test method, this study investigated the spatiotemporal distribution of vegetation recovery potential in northwest China and its relationship with global warming and increasing precipitation. The results indicated that vegetation in northwest China significantly increased, with greening closely related to trends in warming and wetting during 1982-2019. However, the vegetation recovery potential declined due to climate change. Central and southern Xinjiang and central Qinghai exhibited higher grassland recovery potential, while the central Gobi Desert areas of northwest China had lower recovery potential. The eastern part of northwest China was highly sensitive to drought, with moderate vegetation growth and recovery potential. Remote sensing data indicated a 2.3% increase in vegetation coverage in the region, with an average vegetation recovery potential index (IVCP) of 0.31. According to the results of LPJ model, the average vegetation recovery potential index for northwest China was 0.14, indicating a 1.1% improvement potential in vegetation coverage. Overall, climate warming and wetting facilitated vegetation recovery in northwest China, particularly in mountainous areas. The findings provide valuable insights for ecological restoration efforts and offer practical guidance for combating desertification and enhancing sustainable development. Moreover, these results underline the importance of incorporating vegetation recovery potential into regional policy-making to improve environmental resilience in the face of ongoing climate change.

Exploring the Bioactive Potential of Pinus mugo Turra Essential Oil: Volatile Composition, Antioxidant, Antimicrobial, Antibiofilm and Insecticidal Activities

ABSTRACTPinus represents a potential source of valuable bioactive substances. In this study, the chemical composition and biological activity of essential oils extracted from Pinus mugo Turra needles (PMEO) were investigated. GC/MS analyses were used to assess the volatile elements found in the PMEO sample. The antioxidant activity was evaluated using DPPH and ABTS techniques. Antimicrobial properties were evaluated against yeasts and bacteria (both Gram‐positive and Gram‐negative) using the disc diffusion method, minimal inhibition concentration and vapour phase on fruit and vegetable models. Mass spectrometry and the crystal violet technique were used to measure the antibiofilm activity. The contact application method was used to assess the insecticidal activity of different concentration of PMEO against Harmonia axyridis. The GC/MS analysis identified β‐phellandrene (20.5%), α‐pinene (19.4%), δ‐3‐carene (16.7%), β‐pinene (11.1%) and β‐myrcene (9.4%) as main constituents. PMEO exhibited antioxidant activity against DPPH and ABTS radical species, with IC50 values of 1.92 and 1.14 mg/mL, respectively. PMEO showed an inhibitory effect against microbial strains ranging from 6.67 to 13.33 mm. By employing the microdilution method, PMEO showed antimicrobial activity with MIC50 values ranging from 2.52 to 7.41 mg/mL and MIC90 values ranging from 2.72 to 7.7 mg/mL. The in situ antimicrobial investigations revealed that PMEO exerts the highest activity against E. aerogenes and P. putida on apple and beetroot models. Furthermore, PMEO exhibited noteworthy potential against biofilm‐forming S. enterica growing on plastic and glass surfaces. Additionally, an evaluation of the PMEO insecticidal potential was performed using H. axyridis. Insecticidal properties against H. axyridis were observed at concentrations of 50% and 100%. PMEO displayed good antioxidant, antibacterial and insecticidal properties, significant antibiofilm features and excellent preservative properties for extending the shelf life of foods.

Resilience Indicators for Tropical Rainforests in a Dynamic Vegetation Model.

Tropical forests and particularly the Amazon rainforest have been identified as potential tipping elements in the Earth system. According to a dynamical systems theory, a decline in forest resilience preceding a potential shift to a savanna-like biome could manifest as increasing autocorrelation of biomass time series. Recent satellite records indeed exhibit such a trend and also show larger autocorrelation, indicative of reduced resilience, in drier forest regions. However, it is unclear which processes underlie these observational findings and on which scales they operate. Here, we investigate which processes determine tropical forest resilience in the stand-alone, state-of-the-art dynamic global vegetation model LPJmL. We find that autocorrelation is higher in dry climates than wet climates (approx. 0.75 vs. 0.2, for a lag of 10 years), which qualitatively agrees with observations. By constructing a reduced version of LPJmL and by disabling and enabling certain processes in the model, we show that (i) this pattern is associated with population dynamics operating on different time scales in different climates and (ii) that the pattern is sensitive to the allocation of carbon to different pools, especially in years of stress. Both processes are highly uncertain, oversimplified or even lacking in most Earth system models. Our results indicate that the observed spatial variations and trends in vegetation resilience indicators may be explained by local physiological and ecological mechanisms alone, without climate-vegetation feedbacks. In principle, this is consistent with the view that the Amazon rainforest is responding to climate change locally and does not necessarily need to approach one large-scale tipping point, although the latter cannot be ruled out based on our findings.

Source vs sink limitations on tree growth: from physiological mechanisms to evolutionary constraints and terrestrial carbon cycle implications.

The potential for widespread sink-limited plant growth has received increasing attention in the literature in the past few years. Despite recent evidence for sink limitations to plant growth, there are reasons to be cautious about a sink-limited world view. First, source-limited vegetation models do a reasonable job at capturing geographic patterns in plant productivity and responses to resource limitations. Second, from an evolutionary perspective, it is nonadaptive for plants to invest in increasing carbon assimilation if growth is primarily sink-limited. In this review, we synthesize the potential evidence for and underlying physiology of sink limitation across terrestrial ecosystems and contrast mechanisms of sink limitation with those of source-limited productivity. We highlight evolutionary restrictions on the magnitude of sink limitation at the organismal level. We also detail where mechanisms regulating sink limitation at the organismal and ecosystem scale (e.g. the terrestrial carbon sink) diverge. Although we find that there is currently no direct evidence for widespread organismal sink limitation, we propose a series of follow-up growth chamber manipulations, systematized measurements, and modeling experiments targeted at diagnosing nonadaptive buildup of excess nonstructural carbohydrates that will help illuminate the prevalence and magnitude of organismal sink limitation.

Drivers of global irrigation expansion: the role of discrete global grid choice

Abstract. Global statistical irrigation modeling relies on geospatial data and traditionally adopts a discrete global grid based on longitude–latitude reference. However, this system introduces area distortion, which may lead to biased results. We propose using the ISEA3H geodesic grid based on hexagonal cells, enabling efficient and distortion-free representation of spherical data. To understand the impact of discrete global grid choice, we employ a non-parametric statistical framework, utilizing random forest methods, to identify the main drivers of historical global irrigation expansion using, among other data, outputs from the global dynamic vegetation model Lund-Potsdam-Jena managed Land (LPJml). Irrigation is critical for food security amidst growing populations, changing consumption patterns, and climate change. It significantly boosts crop yields but also alters the water cycle and global water resources. Understanding past irrigation expansion and its drivers is vital for global change research, resource assessment, and the prediction of future trends. We compare predictive accuracy, simulated irrigation patterns, and identification of irrigation drivers between the two grid systems. Using the ISEA3H geodesic grid system increases the predictive accuracy by up to 28 % compared to the longitude–latitude grid. The model identifies population density, potential productivity increase, evaporation, precipitation, and water discharge as key drivers of historical global irrigation expansion. Gross domestic product (GDP) per capita also shows some influence. We conclude that the geodesic discrete global grid system significantly affects predicted irrigation patterns and identification of drivers and thus has the potential to enhance statistical modeling, which warrants further exploration in future research across related fields. This analysis lays the foundation for comprehending historical global irrigation expansion.

Simulated sensitivity of the Amazon rainforest to extreme drought

Abstract The Amazon rainforest is highly biodiverse and the largest intact, tropical forest in the world. Undisturbed tropical forests act as a carbon sink by taking up about 15% of anthropogenic carbon emissions per year. In the past decades, a declining trend in the carbon sink capacity in the Amazon rainforest has been observed due to increased carbon losses and tree mortality. The causes are disputed, but increasing temperatures and more frequent severe droughts are potentially major drivers. We employ a novel modelling framework and hypothesize that previously rare, extreme droughts in the Amazon, such as the ones in 2005 and 2010, constitute the main cause behind the decline of the net carbon sink in aboveground biomass. Our dynamic vegetation model simulates process-based plant hydraulics and drought-induced mortality, and accounts for the diversity of strategies in plant responses to drought based on observed hydraulic vulnerability curves. The simulated impact of the 2005 drought event temporarily turned the annual Amazon net carbon sink to a carbon source of about 0.25 MgC ha-1. In contrast to other dynamic vegetation models our model simulated an increasing trend in carbon losses and a declining trend in the Amazon carbon sink over the past 25 years (net sink rate of -0.018 Mg C ha-1 year-1 or -0.22 Mg C ha-1 per decade) which corresponds well with long-term forest monitoring data (net sink rate of -0.016 Mg C ha-1 year-1). We show that this trend is entirely attributable to drought-induced forest mortality during extreme years. The simulations show a threshold-like behaviour between drought intensity and biomass loss, which is due to xylem vulnerability, indicating the potentially high sensitivity of Amazon forests to extreme drought. Further increases in the severity and frequency of droughts might thus lead to greater carbon release and tree mortality than previously assumed.

Photosynthetic Responses of Peat Moss (Sphagnum spp.) and Bog Cranberry (Vaccinium oxycoccos L.) to Spring Warming.

The rising global temperature makes understanding the impact of warming on plant physiology in critical ecosystems essential, as changes in plant physiology can either help mitigate or intensify climate change. The northern peatlands belong to the most important parts of the global carbon cycle. Therefore, knowledge of the ongoing and future climate change impacts on peatland vegetation photosynthesis is crucial for further refinement of peatland or global carbon cycle and vegetation models. As peat moss (Sphagnum spp.) and bog cranberry (Vaccinium oxycoccos L.) represent some of the most common plant functional groups of peatland vegetation, we examined the impact of experimental warming on the status of their photosynthetic apparatus during the early vegetation season. We also studied the differences in the winter to early spring transition of peat moss and bog cranberry photosynthetic activity. We have shown that peat moss starts photosynthetic activity earlier because it relies on light-dependent energy dissipation through the winter. However, bog cranberry needs a period of warmer temperature to reach full activity due to the sustained, non-regulated, heat dissipation during winter, as suggested by the doubling of photosystem II efficiency and 36% decrease in sustained heat dissipation between the mid-March and beginning of May. The experimental warming further enhanced the performance of photosystem II, indicated by a significant increase in the photosystem II performance index on an absorption basis due to warming. Therefore, our results suggest that bog cranberry can benefit more from early spring warming, as its activity is sped up more compared to peat moss. This will probably result in faster shrub encroachment of the peatlands in the warmer future. The vegetation and carbon models should take into account the results of this research to predict the peatland functions under changing climate conditions.

Shining a new light on the classical concepts of carbon-isotope dendrochronology.

Retrospective information about plant ecophysiology and the climate system are key inputs in Earth system and vegetation models. Dendrochronology provides such information with large spatiotemporal coverage, and carbon-isotope analysis across tree-ring series is among the most advanced dendrochronological tools. For the past 70 years, this analysis was performed on whole molecules and, to this day, 13C discrimination during carbon assimilation is invoked to explain isotope variation and associated climate signals. However, recently it was reported that tree-ring glucose exhibits multiple isotope signals at the intramolecular level (see Wieloch etal., 2024). Here, I estimated the signals' contribution to whole-molecule isotope variation and found that downstream processes in leaf and stem metabolism each introduce more variation than carbon assimilation. Moreover, downstream processes introduce most of the climate information. These findings areinconsistent with the classical concepts/practices of carbon-isotope dendrochronology. More importantly, intramolecular tree-ring isotope analysis promises novel insights into forest metabolism and the climate of the past.

Fire, environmental and anthropogenic controls on pantropical tree cover

Explaining tropical tree cover distribution in areas of intermediate rainfall is challenging, with fire’s role in limiting tree cover particularly controversial. We use a novel Bayesian approach to provide observational constraints on the strength of the influence of humans, fire, rainfall seasonality, heat stress, and wind throw on tropical tree cover. Rainfall has the largest relative impact on tree cover (11.6–39.6%), followed by direct human pressures (29.8–36.8%), heat stress (10.5–23.3%) and rainfall seasonality (6.3–22.8%). Fire has a smaller impact (0.2–3.2%) than other stresses, increasing to 0.3–5.2% when excluding human influence. However, we found a potential vulnerability of eastern Amazon and Indonesian forests to fire, with up to 2% forest loss for a 1% increase in burnt area. Our results suggest that vegetation models should focus on fire development for emerging fire regimes in tropical forests and revisit the linkages between rainfall, non-fire disturbances, land use and broad-scale vegetation distributions.

The key role of forest disturbance in reconciling estimates of the northern carbon sink

Northern forests are an important carbon sink, but our understanding of the driving factors is limited due to discrepancies between dynamic global vegetation models (DGVMs) and atmospheric inversions. We show that DGVMs simulate a 50% lower sink (1.1 ± 0.5 PgC yr−1 over 2001–2021) across North America, Europe, Russia, and China compared to atmospheric inversions (2.2 ± 0.6 PgC yr−1). We explain why DGVMs underestimate the carbon sink by considering how they represent disturbance processes, specifically the overestimation of fire emissions, and the lack of robust forest demography resulting in lower forest regrowth rates than observed. We reconcile net sink estimates by using alternative disturbance-related fluxes. We estimate carbon uptake through forest regrowth by combining satellite-derived forest age and biomass maps. We calculate a regrowth flux of 1.1 ± 0.1 PgC yr−1, and combine this with satellite-derived estimates of fire emissions (0.4 ± 0.1 PgC yr−1), land-use change emissions from bookkeeping models (0.9 ± 0.2 PgC yr−1), and the DGVM-estimated sink from CO2 fertilisation, nitrogen deposition, and climate change (2.2 ± 0.9 PgC yr−1). The resulting ‘bottom-up’ net flux of 2.1 ± 0.9 PgC yr−1 agrees with atmospheric inversions. The reconciliation holds at regional scales, increasing confidence in our results.

Resolving Uncertainty in the Response of Australia's Terrestrial Carbon Cycle to Projected Climate Change

AbstractSemi‐arid ecosystems, common across the Australian continent, strongly influence the inter‐annual variability and trend in the global terrestrial net carbon sink. Here we explore the future Australian terrestrial carbon cycle using the CMIP6 ensemble, and the dynamic global vegetation model LPJ‐GUESS. Uncertainty in Australia's carbon storage in vegetation ranged between 6 and 49 PgC at the end of the century and was strongly linked to biases in the meteorological forcing. Using LPJ‐GUESS with bias‐corrected meteorological forcing reduced uncertainty in the vegetation carbon storage to between 14 and 20 PgC, with the remaining range linked to model sensitivities to rising atmospheric CO2 concentration, temperature, and precipitation variability. Reducing this uncertainty will require improved terrestrial biosphere models, but also major improvements in the simulation of regional precipitation by Global Climate Models.

Chemical Composition, Biological Activity, and Application of Rosa damascena Essential Oil as an Antimicrobial Agent in Minimally Processed Eggplant Inoculated with Salmonella enterica.

Rosa damascena is mostly grown for its usage in the food, medical, and perfume industries, while it is also used as an attractive plant in parks, gardens, and homes. The use of R. damascena essential oil may yield new results in relation to the antimicrobial activity of essential oils and their use mainly in extending the shelf life of foods. This study investigates the chemical composition and antimicrobial properties of Rosa damascena essential oil (RDEO) using gas chromatography-mass spectrometry (GC-MS) and various bioassays to explore its potential applications in food preservation and microorganism growth control. The GC-MS analysis revealed that RDEO is predominantly composed of phenylethyl alcohol (70%), which is known for its antimicrobial and aromatic properties. Additionally, other significant constituents were identified, including nerol, citronellol, and geraniol, which may contribute to the EOs overall bioactivity. The antimicrobial activity was assessed through the minimal inhibition concentration against five Candida yeast strains, four Gram-positive, and four Gram-negative bacteria, including biofilm-forming Salmonella enterica. Determination of minimum inhibitory concentrations (MIC) revealed the strongest effects of RDEO's on Gram-negative species, with MIC50 values as low as 0.250 mg/mL for S. enterica. Moreover, an in situ assessment utilizing fruit and vegetable models demonstrated that the vapor phase of RDEO significantly suppressed microbial growth, with the most substantial reductions observed on kiwi and banana models. As a result of our study, the antimicrobial effect of RDEO on the microbiota of sous vide processed eggplant was detected, as well as an inhibitory effect on S. enterica during storage. The insecticidal activity against Megabruchidius dorsalis Fahreus, 1839, was also studied in this work and the best insecticidal activity was found at the highest concentrations. These results suggest that RDEO has the potential to serve as a natural antimicrobial agent in food preservation and safety applications, providing an alternative to synthetic preservatives.